Global Optimization of Rectennas for IR Energy Harvesting at 10.6<i>μ</i>m
Bibliographic record
Abstract
The impedance mismatch between a rectenna's two components, the antenna and the rectifying diode, represents a serious impediment to improving the rectenna's efficiency. Also, the diode's capacitance and the device equivalent resistance determine the rectenna's cutoff frequency. For the detection of the terahertz-frequency signals, ultrafast rectifying metal-insulator- metal diodes are feasible rectifiers. Here, we investigate the global optimization of the rectenna's efficiency working at 10.6 μm by taking the diode materials' properties into consideration. Our proposed objective function considers the impedance matching between antenna and diode, the device cutoff frequency, and the diode responsivity which governs the rectification efficiency. The optimal parameter set reveals a 5.5% coupling efficiency and a zero-bias responsivity of 6.4 A/W. The desirable material properties and geometry are prescribed. The fabrication of Ti-TiO2/ZnO-Al metal-insulator-insulator-metal diode based on the optimal results is carried out and characterized.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".